Large-scale analysis of numerical data can be an arduous task. Conventional systems provide user interfaces for analyzing data, however, they are extremely limited. In particular, conventional systems for setting up and performing tasks, such as molecular screening, are both inefficient and inflexible.
For example, in conventional systems for creating templates of plates used for screening compounds and probes, the design of the template is fixed. The user has no ability to make changes to the template based on the user's experience and technical expertise. In addition, once results are run, conventional systems are extremely limited in how generated data is displayed. For example, in conventional systems, changes to data may only be accomplished in a tabular view of the data, and the tabular and graphical views of the data may be incapable of displaying simultaneously. The user must constantly switch between the tabular view in which data is entered and the graphical view. Recalculation in such systems is entirely manual.
Another disadvantage with conventional systems is that to date conventional systems have been limited to single computing platforms. For example, a data analysis module may utilize Microsoft Excel for Windows. A system architecture that supports multiple computing platforms in a manner that is transparent to a user is not found in current systems.